1348. Tweet Counts Per Frequency 推特文章的访问频率
1348. Tweet Counts Per Frequency
Medium
A social media company is trying to monitor activity on their site by analyzing the number of tweets that occur in select periods of time. These periods can be partitioned into smaller time chunks based on a certain frequency (every minute, hour, or day).
For example, the period [10, 10000]
(in seconds) would be partitioned into the following time chunks with these frequencies:
- Every minute (60-second chunks):
[10,69]
,[70,129]
,[130,189]
,...
,[9970,10000]
- Every hour (3600-second chunks):
[10,3609]
,[3610,7209]
,[7210,10000]
- Every day (86400-second chunks):
[10,10000]
Notice that the last chunk may be shorter than the specified frequency's chunk size and will always end with the end time of the period (10000
in the above example).
Design and implement an API to help the company with their analysis.
Implement the TweetCounts
class:
TweetCounts()
Initializes theTweetCounts
object.void recordTweet(String tweetName, int time)
Stores thetweetName
at the recordedtime
(in seconds).List<Integer> getTweetCountsPerFrequency(String freq, String tweetName, int startTime, int endTime)
Returns a list of integers representing the number of tweets withtweetName
in each time chunk for the given period of time[startTime, endTime]
(in seconds) and frequencyfreq
.freq
is one of"minute"
,"hour"
, or"day"
representing a frequency of every minute, hour, or day respectively.
Example:
Input
["TweetCounts","recordTweet","recordTweet","recordTweet","getTweetCountsPerFrequency","getTweetCountsPerFrequency","recordTweet","getTweetCountsPerFrequency"]
[[],["tweet3",0],["tweet3",60],["tweet3",10],["minute","tweet3",0,59],["minute","tweet3",0,60],["tweet3",120],["hour","tweet3",0,210]]
Output
[null,null,null,null,[2],[2,1],null,[4]]
Explanation
TweetCounts tweetCounts = new TweetCounts();
tweetCounts.recordTweet("tweet3", 0); // New tweet "tweet3" at time 0
tweetCounts.recordTweet("tweet3", 60); // New tweet "tweet3" at time 60
tweetCounts.recordTweet("tweet3", 10); // New tweet "tweet3" at time 10
tweetCounts.getTweetCountsPerFrequency("minute", "tweet3", 0, 59); // return [2]; chunk [0,59] had 2 tweets
tweetCounts.getTweetCountsPerFrequency("minute", "tweet3", 0, 60); // return [2,1]; chunk [0,59] had 2 tweets, chunk [60,60] had 1 tweet
tweetCounts.recordTweet("tweet3", 120); // New tweet "tweet3" at time 120
tweetCounts.getTweetCountsPerFrequency("hour", "tweet3", 0, 210); // return [4]; chunk [0,210] had 4 tweets
treemap是个好东西啊,可以用于value的排序
class TweetCounts { private Map<String, TreeMap<Integer, Integer>> map; public TweetCounts() { map = new HashMap<>(); } public void recordTweet(String tweetName, int time) { if (!map.containsKey(tweetName)) map.put(tweetName, new TreeMap<>()); TreeMap<Integer, Integer> tweetMap = map.get(tweetName); tweetMap.put(time, tweetMap.getOrDefault(time, 0) + 1); } public List<Integer> getTweetCountsPerFrequency(String freq, String tweetName, int startTime, int endTime) { if (!map.containsKey(tweetName)) return null; List<Integer> res = new LinkedList<>(); int interval = 0, size = 0; if (freq.equals("minute")) { interval = 60; } else if (freq.equals("hour")) { interval = 3600; } else { interval = 86400; } size = ((endTime - startTime) / interval) + 1; int[] buckets = new int[size]; TreeMap<Integer, Integer> tweetMap = map.get(tweetName); for (Map.Entry<Integer, Integer> entry : tweetMap.subMap(startTime, endTime + 1).entrySet()) { int index = (entry.getKey() - startTime) / interval; buckets[index] += entry.getValue(); } for (int num : buckets) res.add(num); return res; } } /** * Your TweetCounts object will be instantiated and called as such: * TweetCounts obj = new TweetCounts(); * obj.recordTweet(tweetName,time); * List<Integer> param_2 = obj.getTweetCountsPerFrequency(freq,tweetName,startTime,endTime); */